Senior Scientist, Computational Biology

About Scribe:

Scribe Therapeutics is a clinical-stage biotechnology company engineering CRISPR-based technologies into purpose-built in vivo genetic medicines designed to become standard of care treatments for patients suffering from highly prevalent diseases, starting with cardiometabolic disease. Leveraging its CRISPR by Design™ approach and nature’s blueprint for improved cardiovascular health, Scribe’s initial programs focus on addressing the key drivers of ASCVD such as elevated LDL-C, lipoprotein(a), and triglycerides. The company’s lead candidate, STX-1150, is a novel liver-targeted therapy designed to epigenetically silence the PCSK9 gene and reduce LDL-C levels without inducing permanent DNA changes. To broaden and accelerate the impact of its engineered CRISPR technologies for patients, Scribe has formed strategic collaborations with world-leading pharmaceutical companies including Sanofi and Eli Lilly. Co-founded by Nobel Prize winner Jennifer Doudna and backed by leading life sciences investors, Scribe is advancing scalable, transformative, and preventative genetic medicines with the goal of improving outcomes and democratizing access to the protective effects of beneficial human genetics.

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Position Summary:

We are looking for a highly creative, passionate, and motivated individual to join us in our quest to develop the next generation of CRISPR-based therapeutics. We are seeking a Senior Scientist in Computational Biology to lead multi-omics data analyses supporting our therapeutic programs and platform development. This is a hands-on scientific role responsible for experiment design, computational analysis, statistical modeling, and biological interpretation. The successful candidate will work closely with colleagues in Discovery, Pharmacology, NGS, and Data Science to characterize therapeutic activity, mechanism of action, and specificity and deliver clear, reproducible analyses that guide program decisions and support regulatory data packages.

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Competencies:

• Computational Biology
• Bioinformatics
• Experiment Design
• Statistical Modeling
• Project Leadership
• Multi-Omics Analysis
• Cross-Functional Collaboration

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Key Duties / Responsibilities / “What you’ll do”:

• Lead bioinformatics analyses of multi-omics datasets, including whole genome sequencing, transcriptomics, epigenomic sequencing, targeted amplicon sequencing, and off-target discovery NGS sequencing to guide gene-editing experiments.
• Develop and maintain version-controlled, reproducible computational pipelines with quality checks and standardized reporting; collaborate with engineering colleagues to support automation and LIMS integration.
• Apply machine learning methods to support target identification and molecular engineering.
• Support NGS assay development and qualification by evaluating analytical performance, sources of variation, and the reliability of biological conclusions.
• Collaborate with cross-functional teams on experiment design, results interpretation, and troubleshooting.
• Demonstrate strong statistical judgment in assessing reproducibility, experimental controls, batch effects, and measurement uncertainty across complex biological datasets.
• Contribute to the planning and delivery of scientific projects, regulatory submissions, and project presentations.

Requirements

Knowledge Requirements (Background/Skills/Experience):

• PhD in Bioinformatics, Computational Biology, Genomics, Biostatistics, or a related field with 3+ years of relevant postdoctoral or industry experience; or a master’s degree with 6+ years of relevant experience.
• Strong hands-on experience analyzing RNA-seq and DNA methylation data, with a track record of translating results into biological insights and experimental decisions.
• Experience analyzing genomic sequencing data, including variant interpretation and assessment of copy number or structural variation.
• Strong grounding in experimental design and statistics, including generalized linear models, mixed-effects models, multiple-testing correction, and interpretation of effect sizes and uncertainty.
• Proficiency in R and Python, Linux command-line tools, and Git, with experience building reproducible workflows using Nextflow, Snakemake, or similar tools.
• Experience with AWS or other cloud computing environments, containers, and Benchling or another LIMS.
• Ability to evaluate sequencing quality, recognize technical artifacts and confounding factors, and explain the limitations of analytical results.
• Demonstrated ability to lead analysis projects independently, manage competing priorities, and collaborate effectively with other scientists.
• Clear written and verbal communication, including the ability to explain complex analyses to colleagues with different scientific backgrounds.

Preferred Qualifications

• Experience in biotechnology or pharmaceutical R&D, particularly CRISPR genome editing, epigenetic regulation, or genetic medicines.
• Experience assessing genome editing outcomes, off-target activity, or genomic integrity using short-read or long-read sequencing.
• Experience with assay qualification, traceable analysis documentation, and data packages supporting regulatory submissions.

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Physical Requirements:

• Prolonged periods of sitting at a desk and working on a computer.
• Must be able to lift up to 15 pounds at times.